This project is a test of the efficacy of a new diagnostic method for imaging the airways known as virtual bronchoscopy. Virtual Bronchoscopy is performed by acquiring thin section computer tomography (CT) images of the chest. These images are used to generate a three-dimensional (3D) model of the tracheal and bronchial walls on a graphics workstation in 3D. The model can be manipulated to allow the viewer to "fly-through" the tracheobronchial tree providing views similar to those obtained using bronchoscopy. The technique produces a display of the human bronchial system in a readily understood format. Moreover, it allows investigation of post-stenotic portions of the bronchial tree that are beyond the reach of fiberoptic bronchoscopy. Further, virtual bronchoscopy may be used to guide interventional procedures. The patients that will be studied in this protocol will be those having inflammatory, infectious, or neoplastic pulmonary processes who would have had chest CT for clinical reasons. These patients will be recruited from current NIH protocols. The study design consists of scanning of the thorax using thin section helical CT, followed by three dimensional surface rendering of the airways and transfer of the digital data to videotape. In one of four parts of the protocol, the virtual bronchoscopy will be compared with results from fiberoptic bronchoscopy in a blinded study. In a second part of the protocol, the virtual bronchoscopy will be used to perform a descriptive analysis of cavity lung lesions. In the third part, the utility of virtual bronchoscopy in diagnosis of neoplastic lesions of the chest will be studied. In the fourth part, certain technical problems in the virtual bronchoscopy procedure will be investigated. The patients will only have fiberoptic bronchoscopy for clinically indicated purposes. We anticipate that virtual bronchoscopy will be diagnostically efficacious for disorders which produce a morphologic alteration in bronchial anatomy. There have been no complications. Virtual bronchoscopy has been shown to be useful for detecting stenoses. We now have access to a CT scanner with higher Z-axis resolution and are investigating its efficacy for virtual bronchoscopy. Data acquisition and analysis are complete. Major publications have already been published. A book chapter (review) was published this year.